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Awards

Topic Information Award/Contract Number Proposal Information Company Performance
Period
Award/Contract
Value
Abstract

H-SB016.1-004
Autonomous Indoor Navigation and Tracking of First Responders

HSHQDC-16-C-00068 HSHQDC-16-R-00012-H-SB016.1-004-0002-I
(HSHQDC-16-R-00012 Phase I)
ANTARES

Robotic Research, LLC
555 Quince Orchard Road, Suite 300
Gaithersburg, MD 20878-1453

05/02/2016
to
11/01/2016
$99,989.49

For the past 10 years, Robotic Research, LLC has worked with the Special Forces community to meet these requirements, and to deploy the resulting systems: WarLoc and Mole. The US government has invested in excess of $10 million to develop such capabilities. Over the years, Robotic Research has also leveraged this technology to match the different mission needs of the Army (e.g. the 2nd Infantry Division in South Korea), DHS Customs and Border Protection/Immigration and Customs Enforcement (Nogales group), and the Department of Energy. In this proposal, we will make the case that the core technology developed for these elite customers can be leveraged to provide similar levels of functionality in a package, form factor, and interface that is well-suited for the missions and op-tempo of the first responder community. It is our goal to maintain compatibility with WarLoc and Mole so that interoperability between first responder groups and DoD, DoE, and CBP/ICE can be maintained, and possibly enhanced. We call this technology ANTARES (Autonomous Navigation and Tracking of first RESponders).

H-SB016.1-006
Low-Cost, Real-Time Data Analytics for Underserved EMS Agencies

HSHQDC-16-C-00078 HSHQDC-16-R-00012-H-SB016.1-006-0009-I
(HSHQDC-16-R-00012 Phase I)
EMS Data Analytics in Real-time (EMS DART)

ElanTech
9250 Bendix Road
Suite 1030
Columbia, MD 21045-1832

05/02/2016
to
11/01/2016
$99,998.46

The purpose of this research is to demonstrate the feasibility of developing an architecture design for a real-time monitoring, analysis, and notification solution for underserved EMS organizations at an affordable cost. Two efforts will be completed as part of the proposed research: 1) High performance EMS organizations of different sizes and constraints will be researched to identify a common set of key performance indicators (KPIs). 2) Database technologies and methods will be researched to determine the optimal approach to extracting information from a database with minimum knowledge of its structure and contents. The proposed research efforts will produce a common set of KPIs against which EMS organizations of different sizes and constraints can measure performance, and which can be used by DHS to develop guidance and best practices for operations management. The database research will produce a foundation for developing an automated database query method necessary to develop an analytics solution available to underserved EMS organizations at an affordable cost. Ambulance companies, community based and regional EMS organizations, 9-1-1 dispatch centers, and hospital based dispatch centers are all public safety organizations which would benefit from the proposed research. This market represents tens of thousands of organizations that would benefit from the proposed research. By identifying common high performing EMS KPIs and providing an affordable solution for underserved EMS organizations, the level of patient care will be elevated.

H-SB016.1-007
Real-Time Assessment of Resilience and Preparedness

HSHQDC-16-C-00069 HSHQDC-16-R-00012-H-SB016.1-007-0021-I
(HSHQDC-16-R-00012 Phase I)
RIDER on the Storm: A Cogntive Cloud for Resilience Assessment

Datanova Scientific LLC
3000 Chestnut Ave, Suite 109A
Baltimore, MD 21211-2796

05/02/2016
to
11/01/2016
$98,330.79

We propose Real-time Intelligent Determination of Resilience (RIDER), a cognitive cloud product that consumes real-time data to generate a predictive and proactive risk and resilience posture with site-specific granularity. RIDER utilizes existing FEMA resources in a novel and innovative way for site-specific predictive and proactive risk generation. This statistical risk will be combined with prioritized open data sources (like Twitter) to generate an accurate and current resilience assessment. RIDER will utilize cognitive computing to exploit the open data sources and the FEMA data. The various datasets will be fused together using a deductive semantic model. The RIDER product will produce various visualizations such as heat maps to assess overall resilience of a community. It will also be able to zoom into a specific site or infrastructural component, and be able to provide a detailed logical proof of what affected that site's resilience; this feature is important for the end user to obtain insight from the system. RIDER will also be able to ascertain the conditions under which the risk is acceptable or unacceptable for a given site. The proposed solution addresses the urgent need for resilience assessment in various markets like local governments, the DoD, and commercial insurance companies. Local governments can use RIDER to assess their community's resilience. The DoD is interested in protecting its mission critical infrastructure in various global force deployments. Flood insurance in coastal communities can be optimized greatly using the site-specific, granular, and real time operation of RIDER.

H-SB016.1-008
Using Social Media to Support Timely and Targeted Emergency Response Actions

HSHQDC-16-C-00057 HSHQDC-16-R-00012-H-SB016.1-008-0014-I
(HSHQDC-16-R-00012 Phase I)
Social Media and CAD Correlation (SMaCC)

ElanTech
9250 Bendix Road
Suite 1030
Columbia, MD 21045-1832

05/02/2016
to
11/01/2016
$99,860.19

The purpose of the research is to demonstrate the feasibility of using social media to improve situational awareness and support decision making, pre-emptive response, and predicted outcomes for operational response by first responders. Through customer discovery and literature research, a selected set of Meaningful Events will be identified that, if supported by corroborated data, would provide improved operational responses. Specific social media and computer aided dispatch (CAD) feeds will be identified. The broader factors/triggers supporting and validating Meaningful Events will be discovered. Research the availability of tools and technologies that may support correlated data analytics. Research and document the ways in which correlated data may support operational response(s). Results of this research will include Meaningful Events, validated and supported by potential customer interviews. Once the Meaningful Events are defined, the broader factors and triggers enabling correlation between CAD data and social media data would be identified. The correlated results that support operational response capabilities will be determined. Potential use of correlated data by command and control for operational response, situational awareness and decision making will be documented. First responder, public safety and other organizations would have a tool that could quantify, validate, correlate and present supportive, action-oriented decision support tools around Meaningful Events. This process could enable first responders to modify and enhance the way they respond to mass casualty incidents, and other emergency situations using social media to expand their visibility into events as they occur, in real-time.